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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Page: 1 2 3 4 5...46 Hits 1 – 20 of 906 1 A Bottleneck Auto-Encoder for F0 Transformations on Speech and Singing Voice Bous, Frederik; Roebel, Axel In: ISSN: 2078-2489 ; Information ; https://hal.archives-ouvertes.fr/hal-03599085 ; Information, MDPI, 2022, 13 (3), pp.102. ⟨10.3390/info13030102⟩ (2022) BASE Show details 2 Neural Vocoding for Singing and Speaking Voices with the Multi-Band Excited WaveNet Roebel, Axel; Bous, Frederik In: ISSN: 2078-2489 ; Information ; https://hal.archives-ouvertes.fr/hal-03599076 ; Information, MDPI, 2022, 13 (3), pp.103. ⟨10.3390/info13030103⟩ (2022) BASE Show details 3 Learning and controlling the source-filter representation of speech with a variational autoencoder Sadok, Samir; Leglaive, Simon; Girin, Laurent... In: https://hal.archives-ouvertes.fr/hal-03650569 ; 2022 (2022) BASE Show details 4 A comparative study of several parameterizations for speaker recognition ... Faundez-Zanuy, Marcos. - : arXiv, 2022 BASE Show details 5 Speaker verification in mismatch training and testing conditions ... Faundez-Zanuy, Marcos; Slupinski, Adam. - : arXiv, 2022 BASE Show details 6 Speech Segmentation Optimization using Segmented Bilingual Speech Corpus for End-to-end Speech Translation ... Fukuda, Ryo; Sudoh, Katsuhito; Nakamura, Satoshi. - : arXiv, 2022 BASE Show details 7 A New Amharic Speech Emotion Dataset and Classification Benchmark ... Retta, Ephrem A.; Almekhlafi, Eiad; Sutcliffe, Richard. - : arXiv, 2022 BASE Show details 8 The Norwegian Parliamentary Speech Corpus ... Solberg, Per Erik; Ortiz, Pablo. - : arXiv, 2022 BASE Show details 9 Subspace-based Representation and Learning for Phonotactic Spoken Language Recognition ... Lee, Hung-Shin; Tsao, Yu; Jeng, Shyh-Kang. - : arXiv, 2022 BASE Show details 10 LPC Augment: An LPC-Based ASR Data Augmentation Algorithm for Low and Zero-Resource Children's Dialects ... Johnson, Alexander; Fan, Ruchao; Morris, Robin. - : arXiv, 2022 BASE Show details 11 Automatic Dialect Density Estimation for African American English ... Johnson, Alexander; Everson, Kevin; Ravi, Vijay. - : arXiv, 2022 BASE Show details 12 End-to-end contextual asr based on posterior distribution adaptation for hybrid ctc/attention system ... Zhang, Zhengyi; Zhou, Pan. - : arXiv, 2022 BASE Show details 13 Towards Contextual Spelling Correction for Customization of End-to-end Speech Recognition Systems ... Wang, Xiaoqiang; Liu, Yanqing; Li, Jinyu. - : arXiv, 2022 BASE Show details 14 SHAS: Approaching optimal Segmentation for End-to-End Speech Translation ... Tsiamas, Ioannis; Gállego, Gerard I.; Fonollosa, José A. R.. - : arXiv, 2022 BASE Show details 15 Automatic Detection of Speech Sound Disorder in Child Speech Using Posterior-based Speaker Representations ... Ng, Si-Ioi; Ng, Cymie Wing-Yee; Wang, Jiarui. - : arXiv, 2022 BASE Show details 16 Towards a Perceptual Model for Estimating the Quality of Visual Speech ... Aldeneh, Zakaria; Fedzechkina, Masha; Seto, Skyler. - : arXiv, 2022 BASE Show details 17 Learning and controlling the source-filter representation of speech with a variational autoencoder ... Sadok, Samir; Leglaive, Simon; Girin, Laurent; Alameda-Pineda, Xavier; Séguier, Renaud. - : arXiv, 2022 Abstract: Understanding and controlling latent representations in deep generative models is a challenging yet important problem for analyzing, transforming and generating various types of data. In speech processing, inspiring from the anatomical mechanisms of phonation, the source-filter model considers that speech signals are produced from a few independent and physically meaningful continuous latent factors, among which the fundamental frequency $f_0$ and the formants are of primary importance. In this work, we show that the source-filter model of speech production naturally arises in the latent space of a variational autoencoder (VAE) trained in an unsupervised manner on a dataset of natural speech signals. Using only a few seconds of labeled speech signals generated with an artificial speech synthesizer, we experimentally illustrate that $f_0$ and the formant frequencies are encoded in orthogonal subspaces of the VAE latent space and we develop a weakly-supervised method to accurately and independently control ... : 17 pages, 4 figures, companion website: https://samsad35.github.io/site-sfvae/ ... Keyword: Audio and Speech Processing eess.AS; FOS Computer and information sciences; FOS Electrical engineering, electronic engineering, information engineering; Machine Learning cs.LG; Sound cs.SD URL: https://arxiv.org/abs/2204.07075 https://dx.doi.org/10.48550/arxiv.2204.07075 BASE Hide details 18 Repeat after me: Self-supervised learning of acoustic-to-articulatory mapping by vocal imitation ... Georges, Marc-Antoine; Diard, Julien; Girin, Laurent. - : arXiv, 2022 BASE Show details 19 Can Social Robots Effectively Elicit Curiosity in STEM Topics from K-1 Students During Oral Assessments? ... Johnson, Alexander; Martin, Alejandra; Quintero, Marlen. - : arXiv, 2022 BASE Show details 20 Expression-preserving face frontalization improves visually assisted speech processing ... Kang, Zhiqi; Sadeghi, Mostafa; Horaud, Radu. - : arXiv, 2022 BASE Show details Page: 1 2 3 4 5...46

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